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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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These are energy analytics top areas to focus

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energy analytics
Energy Analytics is a new area started recently. The below are the key points in analytics.

According to Siemens, Outsource your energy data management as a service and benefit from regular analyses performed by our energy experts. Evaluations show that this service makes it possible to easily achieve savings potential of as much as 5 percent.

Headlines of energy analytics

  • Market Forecast: Energy Data & Analytics
  • Energy Data Management & Analytics Business Skills
  • Big Data in an Utilities Environment: Real Case Studies
  • Advantages of Big Data & Analytics: Smart Metering & Cloud Computing
  • Innovative Solutions & Technologies
  • Data Analytics in a Smart Grid Perspective - DONG Energy Case Study
  • Big Data in the TSO Business
  • Achieving Benefits From Smart Meters Deployment With Advanced Analytics - Return on Experience From Large Scale Deployments in the US
  • Smart Grid Cybersecurity, Frameworks and Standards
  • Adopting Open Source Software in Energy Analysis
  • Data Analytics: The Backbone of the Emerging Smart City

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